Design of a new nonlinear model predictive fault tolerant control system using multi-sensor data fusion technique based on UKF algorithm
ISSN: 0332-1649
Article publication date: 6 July 2015
Issue publication date: 6 July 2015
Abstract
Purpose
There are high expectations for reliability, safety and fault tolerance are high in chemical plants. Control systems are capable of potential faults in the plant processing systems. This paper proposes is a new Fault Tolerant Control (FTC) system to identify the probable fault occurrences in the plant.
Design/methodology/approach
A Fault Diagnosis and Isolation (FDI) module has been devised based on the estimated state of system. An Unscented Kalman Filter (UKF) is the main innovation of the FDI module to identify the faults. A Multi-Sensor Data Fusion algorithm is utilized to integrate the UKF output data to enhance fault identification. The UKF employs an augmented state vector to estimate system states and faults simultaneously. A control mechanism is designed to compensate for the undesirable effects of the detected faults.
Findings
The performance of the Nonlinear Model Predictive Controller (NMPC) without any fault compensation is compared with the proposed FTC scheme under different fault scenarios. Analysis of the simulation results indicates that the FDI method is able to identify the faults accurately. The proposed FTC approach facilitates recovery of the closed loop performance after the faults have been isolated.
Originality/value
A significant contribution of the paper is the design of an FTC system by using UKF to estimate faults and enhance the accuracy of data. This is done by applying a data fusion algorithm and controlling the system by the NMPC after eliminating the effects of faults.
Keywords
Acknowledgements
Retraction Notice: The publishers of COMPEL - The international journal for computation and mathematics in electrical and electronic engineering wish to retract the article “Design of a new nonlinear model predictive fault tolerant control system using multi-sensor data fusion technique based on UKF algorithm”, by Mohammad Ghesmat and Akbar Khalkhali, which appeared in volume 34, issue 4, 2015.
It has come to our attention that a large portion of this article is taken, without attribution, from a dissertation submitted to the Petroleum University of Technology by Shabnam Salehi in 2010, “Model Predictive Fault-Tolerant Control of Industrial Chemical Plants using an Adaptive KF-based Multi-Sensor Data Fusion Scheme”.
COMPEL - The international journal for computation and mathematics in electrical and electronic engineering submission guidelines make it clear that articles must be original and must not infringe any existing copyright. The publishers of the journal sincerely apologise to the readers and the original author.
Citation
Ghesmat, M. and Khalkhali, A. (2015), "Design of a new nonlinear model predictive fault tolerant control system using multi-sensor data fusion technique based on UKF algorithm", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 34 No. 4, pp. 1286-1301. https://doi.org/10.1108/COMPEL-10-2014-0274
Publisher
:Emerald Group Publishing Limited
Copyright © 2015, Emerald Group Publishing Limited